Numéro de la revue: 26
Auteurs: Bachir Sakaa1, Hicham Chaffai1, Badra Aoun Sebaiti2, Azzedine Hani1
1 Laboratoire Ressource en Eau et Développement Durable, Département de Géologie, Faculté des Sciences de la Terre, Université Badji Mokhtar, BP 12, 23000 Annaba, Algérie.
2 Département de Génie Civil, Faculté de Technologie, Université 20 Aout 1955, BP 26, Route d’El Hadaiek, 21000 Skikda, Algérie.
This study focuses on determining the most important intervention in technical and managerial policy response category of Integrated Water Resources Management in the Saf-Saf river basin characterized by the fast growing demand of populations and economic sectors including industry and agriculture. The artificial neural networks models were used to model and predict the relationship between water resources mobilization WRM and response variables in the Saf-Saf river basin, where real data were collected from thirty municipalities for reference year 2010.The results indicate that the feed forward multilayer perceptron models with back propagation are useful tools to define and prioritize the most effective response variable on water resources mobilization to intervene and solve water problems. The model evaluation shows that the correlation coefficients are more than 96% for training, verification and testing data. The model aims at linking the water resources mobilization and response variables with the objective to strengthen the Integrated Water Resources Management approach.
Key words: Saf-Saf river basin – Response variables – Water Resources Mobilization – Integrated Water Resources Management – Multilayer perceptron